|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- clinc_oos |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distilbert-base-uncased-distilled-clinc |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: clinc_oos |
|
type: clinc_oos |
|
args: plus |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9419354838709677 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# distilbert-base-uncased-distilled-clinc |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1662 |
|
- Accuracy: 0.9419 |
|
|
|
## Model description |
|
|
|
More information needed |
|
|
|
## Intended uses & limitations |
|
|
|
More information needed |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 2e-05 |
|
- train_batch_size: 48 |
|
- eval_batch_size: 48 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.4626 | 1.0 | 318 | 0.9384 | 0.7232 | |
|
| 0.7233 | 2.0 | 636 | 0.4417 | 0.8648 | |
|
| 0.375 | 3.0 | 954 | 0.2598 | 0.9181 | |
|
| 0.2407 | 4.0 | 1272 | 0.2047 | 0.9323 | |
|
| 0.1932 | 5.0 | 1590 | 0.1859 | 0.9394 | |
|
| 0.1732 | 6.0 | 1908 | 0.1769 | 0.9377 | |
|
| 0.162 | 7.0 | 2226 | 0.1718 | 0.9410 | |
|
| 0.156 | 8.0 | 2544 | 0.1684 | 0.9410 | |
|
| 0.1523 | 9.0 | 2862 | 0.1669 | 0.9416 | |
|
| 0.1502 | 10.0 | 3180 | 0.1662 | 0.9419 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.11.3 |
|
- Pytorch 1.11.0 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.10.3 |
|
|
